Interactive Map
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oil_spill <- read_sf(here("_posts","2021-03-13-spatial-analysis-of-oil-spills-in-california", "data"), layer = "ds394") %>%
clean_names()
ca_counties <- read_sf(here("_posts","2021-03-13-spatial-analysis-of-oil-spills-in-california","ca_counties"), layer = "CA_Counties_TIGER2016") %>%
clean_names()
# st_crs(oil_spill)
# st_crs(ca_counties)
oil_spill <- st_transform(oil_spill, st_crs(ca_counties))
oil_spill_duplicate <- oil_spill %>%
get_dupes(latitude, longitude)
# st_crs(oil_spill)
tmap_mode("view")
tm_shape(oil_spill) +
tm_dots(aes(color = "#700e01")) +
tm_basemap("Esri.NatGeoWorldMap")
Figure 1. Map of oil spills in California in 2008. Each dot represents one location of an oil spill.
Oil spills by county
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oil_count <- oil_spill %>%
count(localecoun)
oil_count_join <- ca_counties %>%
st_join(oil_count)
ggplot(oil_count_join) +
geom_sf(aes(fill = n)) +
theme_void() +
scale_fill_gradientn(colors = c("mistyrose1","lightsalmon3", "lightsalmon4")) +
labs(fill = "Number of Oil Spills") +
annotation_scale(pad_x = unit(2, "cm"), aes(unit_category = "imperial", style = "bar")) +
annotation_north_arrow(height = unit(1.5, "cm"), width = unit(1.5, "cm"), style = north_arrow_nautical())
Figure 1: Figure 2. Oil spill counts by county in 2008. Darker colored counties had higher numbers of oil spills and counties with no data are shown in grey.